docs: fixed broken links

README.md

@@ -42,7 +42,7 @@ See the [official docs page](https://docs.celestia.org/how-to-guides/nodes-overv
 
 ## Supported architectures
 
-Celestia-app officially supports the following architectures:
+Celestia-node officially supports the following architectures:
 
 - `linux/amd64`
 - `linux/arm64`

api/client/readme.md

@@ -125,4 +125,4 @@ balance, err := celestiaClient.State.Balance(ctx)
 
 ## Example
 
-See [example.go](https://github.com/celestiaorg/celestia-node/blob/light-lib/api/client/example/example.go) for a complete example of creating a client, submitting a blob, and retrieving it.
+See [example.go](https://github.com/celestiaorg/celestia-node/blob/main/api/client/example/example.go) for a complete example of creating a client, submitting a blob, and retrieving it.

docs/adr/adr-010-incentivized-testnet-monitoring.md

@@ -14,7 +14,7 @@
 
 ## Context
 
-We're adding telemetry to celestia-node by instrumenting our codebase with metrics (see [ADR-009-telemetry](./adr-009-telemetry.md)). If the option to report metrics is enabled on celestia-node, then celestia-node will push metrics via [OTLP Exporter](https://opentelemetry.io/docs/reference/specification/protocol/exporter/) to an [OTEL Collector](https://opentelemetry.io/docs/collector/) instance.
+We're adding telemetry to celestia-node by instrumenting our codebase with metrics (see [ADR-009-telemetry](../../docker/telemetry)). If the option to report metrics is enabled on celestia-node, then celestia-node will push metrics via [OTLP Exporter](https://opentelemetry.io/docs/reference/specification/protocol/exporter/) to an [OTEL Collector](https://opentelemetry.io/docs/collector/) instance.
 
 We would like to make the metrics exported by celestia-node actionable by making them queryable in internal Grafana dashboards. We additionally want a subset of metrics to be queryable by a public incentivized testnet leaderboard frontend.
 
@@ -28,7 +28,7 @@ This document proposes a strategy for making data available for use in internal
 
 Grafana can query data from [multiple data sources](https://grafana.com/docs/grafana/latest/datasources/#supported-data-sources). This document explores two of these data sources:
 
-1. [Prometheus](https://github.com/prometheus/prometheus) is an open-source time series database written in Go. Prometheus uses the [PromQL](https://prometheus.io/docs/prometheus/latest/querying/basics/) query language. We can deploy Prometheus ourselves or use a hosted Prometheus provider (ex. [Google](https://cloud.google.com/stackdriver/docs/managed-prometheus), [AWS](https://aws.amazon.com/prometheus/), [Grafana](https://grafana.com/go/hosted-prometheus-monitoring/), etc.). Prometheus is pull-based which means services that would like to expose Prometheus metrics must provide an HTTP endpoint (ex. `/metrics`) that a Prometheus instance can poll (see [instrumenting a Go application for Prometheus](https://prometheus.io/docs/guides/go-application/)). Prometheus is used by [Cosmos SDK telemetry](https://docs.cosmos.network/main/learn/advanced/telemetry) and [Tendermint telemetry](https://docs.tendermint.com/main/tendermint-core/metrics.html) so one major benefit to using Prometheus is that metrics emitted by celestia-core, celestia-app, and celestia-node can share the same database.
+1. [Prometheus](https://github.com/prometheus/prometheus) is an open-source time series database written in Go. Prometheus uses the [PromQL](https://prometheus.io/docs/prometheus/latest/querying/basics/) query language. We can deploy Prometheus ourselves or use a hosted Prometheus provider (ex. [Google](https://cloud.google.com/stackdriver/docs/managed-prometheus), [AWS](https://aws.amazon.com/prometheus/), [Grafana](https://grafana.com/go/hosted-prometheus-monitoring/), etc.). Prometheus is pull-based which means services that would like to expose Prometheus metrics must provide an HTTP endpoint (ex. `/metrics`) that a Prometheus instance can poll (see [instrumenting a Go application for Prometheus](https://prometheus.io/docs/guides/go-application/)). Prometheus is used by [Cosmos SDK telemetry](https://docs.cosmos.network/main/learn/advanced/telemetry) and [Tendermint telemetry](https://docs.tendermint.com/master/nodes/metrics.html) so one major benefit to using Prometheus is that metrics emitted by celestia-core, celestia-app, and celestia-node can share the same database.
 2. [InfluxDB](https://github.com/influxdata/influxdb) is another open-source time series database written in Go. It is free to deploy InfluxDB but there is a commercial offering from [influxdata](https://www.influxdata.com/get-influxdb/) that provides clustering and on-prem deployments. InfluxDB uses the [InfluxQL](https://docs.influxdata.com/influxdb/v1.8/query_language/) query language which appears less capable at advanced queries than PromQL ([article](https://www.robustperception.io/translating-between-monitoring-languages/)). InfluxDB is push-based which means services can push metrics directly to an InfluxDB instance ([ref](https://logz.io/blog/prometheus-influxdb/#:~:text=InfluxDB%20is%20a%20push%2Dbased,and%20Prometheus%20fetches%20them%20periodically.)). See [Prometheus vs. InfluxDB](https://prometheus.io/docs/introduction/comparison/#prometheus-vs-influxdb) for a more detailed comparison.
 
 If alternative data sources should be evaluated, please share them with us.